Curriculum

GBA478 covers the application of generative AI technologies across diverse business contexts. The course will help you understand how to integrate Generative AI into today’s business workflows, providing frameworks to decide when and how to use it effectively. You’ll gain hands-on experience designing Generative AI tools to create business value and programming basic LLM-driven applications in Python. Finally, the course will ask you to become conversant with the big questions about Generative AI, to debate the moral, philosophical, and ethical challenges inherent in these systems and technologies.
 

Pricing is one of the most important, least understood, and most controversial decisions a manager has to make. These decisions often have significant long-term implications for a firm’s bottom line. The purpose of this course is to help future managers make good decisions by preparing them to analyze the environment in which their firm operates and to arrive at an appropriate pricing policy for their product or service. More specifically, the objectives of the course are: 1) to develop an understanding of the relationship between a firm’s environment (e.g., cost, demand, competition, and legal aspects) and its optimal pricing strategy, and 2) to develop skills in applying this understanding.

Operations Management introduces the concepts and skills needed to design, manage, and improve service and manufacturing operations. The course develops a managerial perspective of the operations function and an appreciation of the role that operations plays in creating and maintaining a firm’s competitive edge. The course introduces process analysis, performance measurement systems for operations, and production control systems.

This course is designed to provide students with concepts and skills in managing data using traditional and cloud based systems. The course covers theory of database systems, data manipulation techniques, data integration and cleaning, and working with modern and advanced data architectures. The class covers both theory and hands on activities using Microsoft Access, SQL, Tableau and R. Microsoft Access, SQL, Tableau and R may be used extensively in class, for assignments and exams.

This course aims to train practitioners of analytics methods to construct, evaluate, and apply machine learning (ML) models in a variety of business applications using modern tools. The course covers programming tools for handling data, computational frameworks, cloud platforms, and an array of advanced ML algorithms. The course emphasizes hands-on work through class exercises, homework assignments, and projects. The course is self-contained, but basic programming skills are required.

This course introduces the field of AI to business students with a particular emphasis on deep learning which is driving the current AI revolution. The course consists of three modules. The first module establishes the foundation of AI and deep learning. The second module introduces major neural network architectures widely used in practice. The third module touches on generative AI which is particularly promising in recent years. The course emphasizes experiential learning and contains many hands-on projects using TensorFlow broadly and Keras in particular.

This course expands and develops students’ analytical tool kit through “hands on” training in the effective use of spreadsheet-based tools for advanced managerial analysis. Students perform quantitative analysis of advanced problems. The course enhances and reinforces the analytical skills taught in previous modeling coursework such as formulating and solving large-scale business problems using quantitative models, risk simulation and sensitivity analysis. Spreadsheet tools introduced in this class include optimization and simulation. Students who successfully complete the course should possess cutting-edge skills in spreadsheet business modeling and analysis.

This course delves into the multifaceted landscape of financial risk management, covering a broad range of topics including market risk, credit risk, liquidity risk, and operational risk. Through a combination of theoretical frameworks, case studies, and practical applications, students will develop a deep understanding of the various types of risks faced by corporations and financial institutions, as well as the tools and methodologies employed to manage them effectively.

GBA478 covers the application of generative AI technologies across diverse business contexts. The course will help you understand how to integrate Generative AI into today’s business workflows, providing frameworks to decide when and how to use it effectively. You’ll gain hands-on experience designing Generative AI tools to create business value and programming basic LLM-driven applications in Python. Finally, the course will ask you to become conversant with the big questions about Generative AI, to debate the moral, philosophical, and ethical challenges inherent in these systems and technologies.

This course covers the design and development of Generative AI-enhanced business applications.  We will discuss a framework for integrating Gen AI tools and capabilities into business processes, tasks and workflows.  Students will learn how to program with Gen AI tools and LLMs using Python and APIs, including methods for dynamic task automation and workflow coordination using agentic design. The course also covers the use of Retrieval-Augmented Generation (RAG) to access private knowledge bases built on organizational data. By the end of the course, students will be equipped with the technical and conceptual skills to design and build generative AI applications tailored to modern business needs.

Product Management requires outstanding business skills, strong cross-functional leadership, and the ability to discover market/customer needs and to develop profitable solutions to meet those needs. It also requires a set of very specific applied skills, and this course is intended to develop those skills.  
 

Students will learn the major differences in pricing strategies between selling to consumers and to other firms which then deal with consumers. The course starts by analyzing the pricing problem of a manufacturer selling to a retailer. We examine the issue of double marginalization, and learn how two-part tariffs get us out of this problem. We also examine different forms of contractual relations—from vertical acquisitions to regular short-term contracts—and potential issues with every form, touching on transfer pricing and outsourcing. In the second part of the course, we analyze a crucial concept of cost pass-through (how much a retailer should decrease the retail price in response to a decrease in the wholesale price) and the effect of manufacturer’s advertising on the retailer and on the channel overall.

This course equips students with the necessary skills to make profitable pricing decisions in complex business environments. Topics include: pricing with constrained supply, pricing in the presence of uncertainty about demand, markdown management, advance selling, pricing on the internet, pricing in the presence of direct or indirect network effects, selling through auctions, and behavioral and ethical aspects of pricing. 

Students will learn the major differences in pricing strategies between selling to consumers and to other firms which then deal with consumers. The course starts by analyzing the pricing problem of a manufacturer selling to a retailer. We examine the issue of double marginalization, and learn how two-part tariffs get us out of this problem. We also examine different forms of contractual relations—from vertical acquisitions to regular short-term contracts—and potential issues with every form, touching on transfer pricing and outsourcing. In the second part of the course, we analyze a crucial concept of cost pass-through (how much a retailer should decrease the retail price in response to a decrease in the wholesale price) and the effect of manufacturer’s advertising on the retailer and on the channel overall.

This course gives an overview of supply chain management in a wide variety of industries such as: groceries, style goods, consumer electronics and services. The impact of shifts from traditional channels to e-commerce will be emphasized. New initiatives introduced to address these new challenges, such as vendor managed inventory (VMI), variety postponement, cross docking, real options contracts and quick response, will be studied and applied both in class and assignments.